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application of the Mathematical model developed by Lutz et al

Posted by plosmedicine on 31 Mar 2009 at 00:28 GMT

Author: Sam Hanash
Position: member
Institution: Fred Hutchinson Cancer Research Center
Submitted Date: August 19, 2008
Published Date: August 19, 2008
This comment was originally posted as a “Reader Response” on the publication date indicated above. All Reader Responses are now available as comments.

The model developed in this paper addresses an important need in the field of cancer biomarkers. Deriving estimates of the balance between tumor biomarker secretion into and removal out of the intravascular compartment that takes into account protein secretion rates by tumor cells is quite useful. In their paper, the authors primed the model based on data available for the ovarian marker CA 125 leading to estimates of the minimal tumor size required to detect elevated levels of CA125 in circulation in ovarian cancer. We have applied this model to proteins that we have identified in ovarian cancer cells to be secreted in a study that was published recently in PLOS One (Faca et al Proteomic analysis of ovarian cancer cells reveals dynamic processes of protein secretion and shedding of extra-cellular domains.
PLoS ONE. 2008 Jun 18;3(6):e2425 ). A case in point is TIMP1, the secretion rate of which was measured in CaOV3 and ES2 cell lines to be ~3 ng/ million cells / h), using the model, we would estimate that a tumor ~ 2cm in diameter would lead to a detectable 50% increase in the level of TIMP1. Assumptions for the calculation are: i) a half-life in blood of 48h, which is significantly below that of CA-125 (151h); ii) 50% of secreted protein reaching the blood. Development a full repertoire of proteins secreted by ovarian cancer cells or other cancer types, with measures of their secretion rates, will allow prioritization of candidates to proceed based on the parameters in the model. Of course the model would be subjected to refinement in the future. However implementing a rational way for assessment of candidate biomarkers would be quite advantageous to the field.

No competing interests declared.